【知识点1】
把一幅图无缝融合到另一幅图里，主要是seamlessClone() 的使用。
seamlessClone( InputArray src, InputArray dst, InputArray mask, Point p, OutputArray blend, int flags);
注意需要三幅图合为一幅图，src与mask抠图（逻辑与，尺寸一致），把抠出的图融合到dst中的p位置处（抠出的图尺寸≤dst图）。p位置也是抠出的图的中心。
3种融合模式flags：NORMAL_CLONE = 1，MIXED_CLONE = 2，MONOCHROME_TRANSFER = 3
1 #include<opencv2\opencv.hpp>
2 #include<iostream>
3
4 using namespace cv;
5 using namespace std;
6
7 int main()
8 {
9 string folder = "cloning/Normal_Cloning/"; //可更换Mixed_Cloning,Monochrome_Transfer目录
10 string original_path1 = samples::findFile(folder + "source1.png");
11 string original_path2 = samples::findFile(folder + "destination1.png");
12 string original_path3 = samples::findFile(folder + "mask.png");
13
14 Mat source = imread(original_path1, IMREAD_COLOR);
15 Mat destination = imread(original_path2, IMREAD_COLOR);
16 Mat mask = imread(original_path3, IMREAD_COLOR);
17
18 Mat result;
19 Point p;
20 p.x = destination.size().width / 2;
21 p.y = destination.size().height / 2;
22
23 seamlessClone(source, destination, mask, p, result, NORMAL_CLONE); //可更换MIXED_CLONE，MONOCHROME_TRANSFER
24
25 imshow("Output", result);
26 imwrite("cloned.png", result);
27
28 waitKey(0);
29 return 0;
30 }
【知识点2】
对感兴趣区域进行颜色调整。如下图，花朵更鲜艳。主要是colorChange()函数的使用。
1 #include<opencv2\opencv.hpp>
2 #include<iostream>
3
4 using namespace cv;
5 using namespace std;
6
7 int main()
8 {
9 string folder = "cloning/color_change/";
10 string original_path1 = samples::findFile(folder + "source1.png");
11 string original_path2 = samples::findFile(folder + "mask.png");
12
13 Mat source = imread(original_path1, IMREAD_COLOR);
14 Mat mask = imread(original_path2, IMREAD_COLOR);
15
16 Mat result;
17 colorChange(source, mask, result, 1.5, .5, .5); //mask定位source中的roi区域，调整该区域颜色r，g，b
18
19 imshow("Output", result);
20 imwrite("cloned.png", result);
21
22 waitKey(0);
23 return 0;
24 }
【知识点3】
消除高亮区域，illuminationChange()函数的使用。alpha，beta两个参数共同决定消除高光后图像的模糊程度（范围0~2，0比较清晰，2比较模糊）
1 #include<opencv2\opencv.hpp>
2 #include<iostream>
3
4 using namespace cv;
5 using namespace std;
6
7 int main()
8 {
9 string folder = "cloning/Illumination_Change/";
10 string original_path1 = samples::findFile(folder + "source1.png");
11 string original_path2 = samples::findFile(folder + "mask.png");
12
13 Mat source = imread(original_path1, IMREAD_COLOR);
14 Mat mask = imread(original_path2, IMREAD_COLOR);
15
16 Mat result;
17
18 illuminationChange(source, mask, result, 0.2f, 0.4f); //消除source中mask锁定的高亮区域，后两个参数0-2调整
19
20 imshow("Output", result);
21 imwrite("cloned.png", result);
22
23 waitKey(0);
24 return 0;
25 }
【知识点4】
纹理扁平化，边缘检测器选取的边缘越少（选择性越强），边缘映射就越稀疏，扁平化效果就越明显。textureFlattening()函数的使用。
1 #include<opencv2\opencv.hpp>
2 #include<iostream>
3
4 using namespace cv;
5 using namespace std;
6
7 int main()
8 {
9 string folder = "cloning/Texture_Flattening/";
10 string original_path1 = samples::findFile(folder + "source1.png");
11 string original_path2 = samples::findFile(folder + "mask.png");
12
13 Mat source = imread(original_path1, IMREAD_COLOR);
14 Mat mask = imread(original_path2, IMREAD_COLOR);
15
16 Mat result;
17
18 textureFlattening(source, mask, result, 30, 45, 3); //对mask锁定的source中的区域进行纹理扁平化，低阈值，高阈值，核尺寸
19
20 imshow("Output", result);
21 imwrite("cloned.png", result);
22
23 waitKey(0);
24 return 0;
25 }
